How does the extent to which a model is open or closed impact the scientific inferences that can be drawn from research that involves it? In this paper, we analyze how restrictions on information about model construction and deployment threaten reliable inference. We argue that current closed models are generally ill-suited for scientific purposes, with some notable exceptions, and discuss ways in which the issues they present to reliable inference can be resolved or mitigated. We recommend that when models are used in research, potential threats to inference should be systematically identified along with the steps taken to mitigate them, and that specific justifications for model selection should be provided.

翻译：模型的开放或封闭程度如何影响从涉及它的研究中得出的科学推断？在本文中，我们分析了模型构建和部署信息方面的限制如何威胁到可靠推断。我们认为，当前封闭模型通常不适合科学研究目的，但存在一些显著例外，并讨论了如何解决或减轻它们对可靠推断带来的问题。我们建议，当模型用于研究时，应系统性地识别对推断的潜在威胁以及为减轻这些威胁所采取的步骤，并提供选择模型的具体理由。